October 2023 arXiv papers — page 128

Martin Braß, Liang Si, Karten Held

We study the impact of spin-orbit coupling on the topological band-properties of copper-substituted lead phosphate apatite using a combination of group-theoretical analysis and full-relativistic density-functional theory calculations. We characterize Weyl points at time-reversal invariant momenta and find that a band-inversion due to spin-orbit coupling lead

Erkan Gunes, Christoffer Koch Florczak

Classifying policy documents into policy issue topics has been a long-time effort in political science and communication disciplines. Efforts to automate text classification processes for social science research purposes have so far achieved remarkable results, but there is still a large room for progress. In this work, we test the prediction performance of

Junyu Lu, Dixiang Zhang, Xiaojun Wu, Xinyu Gao

Recent advancements enlarge the capabilities of large language models (LLMs) in zero-shot image-to-text generation and understanding by integrating multi-modal inputs. However, such success is typically limited to English scenarios due to the lack of large-scale and high-quality non-English multi-modal resources, making it extremely difficult to establish co

Kenan Morani

In here, we introduce a novel approach to enhance the accuracy and efficiency of COVID-19 diagnosis using CT images. Leveraging state-of-the-art Transformer models in computer vision, we employed the base ViT Transformer configured for 224x224-sized input images, modifying the output to suit the binary classification task. Notably, input images were resized

Luke Marks, Amir Abdullah, Clement Neo, Rauno Arike

Reinforcement learning from human feedback (RLHF) is widely used to train large language models (LLMs). However, it is unclear whether LLMs accurately learn the underlying preferences in human feedback data. We coin the term \textit{Learned Feedback Pattern} (LFP) for patterns in an LLM's activations learned during RLHF that improve its performance on the fi

Alessandro Pino, Davide Margaria, Andrea Vesco

The Self-Sovereign Identity (SSI) is a decentralized paradigm enabling full control over the data used to build and prove the identity. In Internet of Things networks with security requirements, the Self-Sovereign Identity can play a key role and bring benefits with respect to centralized identity solutions. The challenge is to make the SSI compatible with r

Tomke E. Glier, Sida Tian, Mika Rerrer, Lea Westphal

Even before its role in electroweak symmetry breaking, the Anderson-Higgs mechanism was introduced to explain the Meissner effect in superconductors. Spontaneous symmetry-breaking yields massless phase modes representing the low-energy excitations of the Mexican-Hat potential. Only in superconductors the phase mode is shifted towards higher energies owing to

Christoph Hofer, Chuang Gao, Tamazouzt Chennit, Biao Yuan

The contrast transfer function of direct ptychography methods such as the single side band (SSB) method are single signed, yet these methods still sometimes exhibit contrast reversals, most often where the projected potentials are strong. In thicker samples central focusing often provides the best ptychographic contrast as this leads to defocus variations wi

Tao Yang, Rong-Gen Cai, Zhoujian Cao, Hyung Mok Lee

The early and precise localization of gravitational waves (GWs) is pivotal in detecting their electromagnetic (EM) counterparts, especially for binary neutron stars (BNS) and neutron star-black hole binaries (NSBH). In this letter, we pioneer the exploration of utilizing the higher harmonic modes induced by the eccentricity of compact binaries to localize GW

Enguerran Belles, Franck Rabilloud, Alexander I. Kuleff, Victor Despré

Correlation-driven charge migration initiated by inner-valence ionization leading to the population of the correlation bands of alkyne chains containing between 4 and 12 carbon atoms is explored through ab initio simulations. Scaling laws are observed, both for the timescale of the charge migration and for the slope of the density of states of the correlatio

Ryusuke Jinno, Kazunori Kohri, Takeo Moroi, Tomo Takahashi

We investigate expected constraints on the primordial tensor power spectrum from the future cosmic microwave background polarization experiment LiteBIRD as a test of multi-field inflation. We argue that the measurements of the tensor-to-scalar ratio and the tensor spectral index, in combination with the constraints on the scalar spectral index from the Planc

Jisung Kim, Byeongjung Lee

Automated program repair (APR) is a technology that identifies and repairs bugs automatically. However, repairing multi-chunk bugs remains a long-standing and challenging problem because an APR technique must consider dependencies and then reduce the large patch space. In addition, little is known about how to combine individual candidate patches even though

Alice Dell'Arciprete

We consider the representation theory of the Ariki-Koike algebra, a $q$-deformation of the group algebra of the complex reflection group $C_r \wr S_n$. We define the addition of a runner full of beads for the abacus display of a multipartition and investigate some combinatorial properties of this operation. We focus our attention on the $q$-decomposition num

Peijin Zhang, Diana Morosan, Anshu Kumari, Emilia Kilpua

Context. Type II radio bursts are solar radio burst associated with coronal shocks. Type II bursts usually exhibit fine structures in dynamic spectra that represent signatures of accelerated electron beams. So far, the sources of individual fine structures in type II bursts have not been spatially resolved in high-resolution low-frequency radio imaging. Aims

Hadrien Kurkjian, Victor E. Colussi, Paul Dyke, Chris J. Vale

We revisit the study of amplitude oscillations in a pair condensate of fermions after an interaction quench, and generalize it to nonzero temperature. For small variations of the order parameter, we show that the energy transfer during the quench determines both the asymptotic pseudo-equilibrated value of the order parameter and the magnitude of the oscillat

Antoine Geimer, Mathéo Vergnolle, Frédéric Recoules, Lesly-Ann Daniel

To protect cryptographic implementations from side-channel vulnerabilities, developers must adopt constant-time programming practices. As these can be error-prone, many side-channel detection tools have been proposed. Despite this, such vulnerabilities are still manually found in cryptographic libraries. While a recent paper by Jancar et al. shows that devel

Siyu Ren, Qi Jia, Kenny Q. Zhu

The quadratic complexity of the attention module makes it gradually become the bulk of compute in Transformer-based LLMs during generation. Moreover, the excessive key-value cache that arises when dealing with long inputs also brings severe issues on memory footprint and inference latency. In this work, we propose a plug-and-play approach that is able to inc

Xinyi Fang, Peng Ren

In this paper, we consider the morphisms from projective spaces to flag varieties. We show that the morphisms can only be constant under some special conditions. As a consequence, we prove that the splitting types of unsplit uniform $r$-bundles on $\mathbb{P}^m$ can not be $(a_1,\dots,a_1,a_2,\dots,a_{r-k+1})$ for $1\le k\le m-2$.

Ansgar Steland

Maximum-type statistics of certain functions of the sample covariance matrix of high-dimensional vector time series are studied to statistically confirm or reject the null hypothesis that a data set has been collected under normal conditions. The approach generalizes the case of the maximal deviation of the sample autocovariances function from its assumed va

Q. Hu, G. Y. Tian, R. Wada, X. Q. Liu

Relativistic corrections have been made in the non-relativistic antisymmetrized molecular dynamics (AMD) simulations to apply to the high energy neutron production in the $^{12}$C+$^{12}$C and $^{16}$O+$^{12}$C collisions at incident energies of 290 and 400 MeV/nucleon. The corrections are made in kinematics alone and no nucleon-nucleon inelastic scatterings

Jingru Gan, Xinzhe Han, Shuhui Wang, Qingming Huang

Given an image and an associated textual question, the purpose of Knowledge-Based Visual Question Answering (KB-VQA) is to provide a correct answer to the question with the aid of external knowledge bases. Prior KB-VQA models are usually formulated as a retriever-classifier framework, where a pre-trained retriever extracts textual or visual information from

Shuaijun Chen, Omid Tavallaie, Michael Henri Hambali, Seid Miad Zandavi

Federated learning (FL) is a novel distributed learning framework designed for applications with privacy-sensitive data. Without sharing data, FL trains local models on individual devices and constructs the global model on the server by performing model aggregation. However, to reduce the communication cost, the participants in each training round are random

Xuan Liu, Jia-Jie Jiang, Xun Chen, Mitsutoshi Fujita

Gauge/gravity duality is used to study properties of the doubly heavy baryon $(\mathrm{QQq})$ at finite rapidity and temperature in the heavy-ion collision. We investigate the impact of rapidity on string breaking and screening of $\mathrm{QQq}$, and compare these effects with the results for $\rm Q\bar{Q}$ in detail. Computations reveal that the string-brea

Antonio Capolupo, Giuseppe De Maria, Simone Monda, Aniello Quaranta

In the framework of quantum field theory, we analyze the neutrino oscillations in the presence of a torsion background. We consider the Einstein-Cartan theory and we study the cases of constant torsion and of linearly time dependent torsion. We derive new neutrino oscillation formulae which are depending on the spin orientation. Indeed the energy splitting i

Yuan Kang, Zong-Hu Li, Zhen-Zhen Kong, Fang-Ge Li

In recent years, notable progress has been made in the study of hole qubits in planar germanium, and circuit quantum electrodynamics (circuit QED) has emerged as a promising approach for achieving long-range coupling and scaling up of qubits. Here, we demonstrate the coupling between holes in a planar germanium double quantum dot (DQD) and photons in a micro

Madieyna Diouf

We have devised an alternative approach to sifting integers in the sieve of Eratosthenes that helps refine the error term. Instead of eliminating all multiples of a prime number $p<z$ in the traditional sieve method, our approach solely eliminates multiples of $p$ that have the minimum prime factor of $p$. By leveraging the density of integers with the least

Léo Milecki, Jonathan Porée, Hatim Belgharbi, Chloé Bourquin

Ultrasound Localization Microscopy can resolve the microvascular bed down to a few micrometers. To achieve such performance microbubble contrast agents must perfuse the entire microvascular network. Microbubbles are then located individually and tracked over time to sample individual vessels, typically over hundreds of thousands of images. To overcome the fu

Xu Chen, Yunde Jia, Yuwei Wu

Face anti-spoofing plays a critical role in safeguarding facial recognition systems against presentation attacks. While existing deep learning methods show promising results, they still suffer from the lack of fine-grained annotations, which lead models to learn task-irrelevant or unfaithful features. In this paper, we propose a fine-grained annotation metho

Samuel Blitz, David McNutt

Motivated by the thermodynamics of black hole solutions conformal to stationary solutions, we study the geometric invariant theory of null hypersurfaces. It is well-known that a null hypersurface in a Lorentzian manifold can be treated as a Carrollian geometry. Additional structure can be added to this geometry by choosing a connection which yields a Carroll

John Ziegler, Fabian Kneissl, Michael Gertz

Conversations are an integral part of online social media, and gaining insights into these conversations is of significant value for many commercial as well as academic use cases. From a computational perspective, however, analyzing conversation data is complex, and numerous aspects must be considered. Next to the structure of conversations, the discussed co

Zehao Wang, Yiwen Guo, Qizhang Li, Guanglei Yang

Data augmentation is a dominant method for reducing model overfitting and improving generalization. Most existing data augmentation methods tend to find a compromise in augmenting the data, \textit{i.e.}, increasing the amplitude of augmentation carefully to avoid degrading some data too much and doing harm to the model performance. We delve into the relatio

Haiyang Liu, Chunjiang Zhu, Detian Zhang, Qing Li

Traffic flow prediction is one of the most fundamental tasks of intelligent transportation systems. The complex and dynamic spatial-temporal dependencies make the traffic flow prediction quite challenging. Although existing spatial-temporal graph neural networks hold prominent, they often encounter challenges such as (1) ignoring the fixed graph that limits

Zhendong Wang, Ioanna Miliou, Isak Samsten, Panagiotis Papapetrou

Among recent developments in time series forecasting methods, deep forecasting models have gained popularity as they can utilize hidden feature patterns in time series to improve forecasting performance. Nevertheless, the majority of current deep forecasting models are opaque, hence making it challenging to interpret the results. While counterfactual explana

Bernold Fiedler

Real vector fields $\dot{z} = f(z)$ in $\mathbb{R}^N$ extend to $\mathbb{C}^N$, for complex entire $f$. One known consequence are exponentially small upper bounds \begin{equation*} \label{*} C_\eta \exp(-\eta/\varepsilon) \tag{*} \end{equation*} on homoclinic splittings under discretizations of step size $\varepsilon>0$, or under rapid forcings of that perio

Thomas Siegert

While the data analysis of $\gamma$-ray telescopes has now become more robust, some signals may be misinterpretations of a time-variable foreground emission from the Solar System, induced by low-energy cosmic-ray interactions with asteroids. Our goal is to provide emission templates for this time-variable diffuse $\gamma$-ray foreground by considering the po

Yanpeng Cui, Qixun Zhang, Zhiyong Feng, Qin Wen

Beam management, including initial access (IA) and beam tracking, is essential to the millimeter-wave Unmanned Aerial Vehicle (UAV) network. However, conventional communication-only and feedback-based schemes suffer a high delay and low accuracy of beam alignment since they only enable the receiver to passively hear the information of the transmitter from th

Robert Wijaya

Predicting the price of a house remains a challenging issue that needs to be addressed. Research has attempted to establish a model with different methods and algorithms to predict the housing price, from the traditional hedonic model to a neural network algorithm. However, many existing algorithms in the literature are proposed without any finetuning and cu

Nick Rossenbach, Benedikt Hilmes, Ralf Schlüter

Synthetic data generated by text-to-speech (TTS) systems can be used to improve automatic speech recognition (ASR) systems in low-resource or domain mismatch tasks. It has been shown that TTS-generated outputs still do not have the same qualities as real data. In this work we focus on the temporal structure of synthetic data and its relation to ASR training.

Satoshi Ishikawa

We investigate the Radon transform for double fibrations of the horocycle spaces for the semisimple symmetric spaces with respect to the inclusion incidence relations. We present the inversion formula, support theorem and the range theorem by the invariant differential operators or the invariant system of differential operators constructed from the left acti

Yuxuan Yao, Han Wu, Qiling Xu, Linqi Song

General-purpose text decoding approaches are usually adopted for dialogue response generation. Although the quality of the generated responses can be improved with dialogue-specific encoding methods, conversational decoding methods are still under-explored. Inspired by \citet{wu2023learning} that a good dialogue feature space should follow the rules of local

Zijie Chen, Lichao Zhang, Fangsheng Weng, Lili Pan

Despite significant progress in the field, it is still challenging to create personalized visual representations that align closely with the desires and preferences of individual users. This process requires users to articulate their ideas in words that are both comprehensible to the models and accurately capture their vision, posing difficulties for many us

José Jaime Terente Díaz, Konstantinos Dimopoulos, Mindaugas Karčiauskas, Antonio Racioppi

Quintessence models have been widely examined in the context of scalar-Gauss-Bonnet gravity, a subclass of Horndeski's theory, and were proposed as viable candidates for Dark Energy. However, the relatively recent observational constraints on the speed of gravitational waves $c_{\textrm{GW}}$ have resulted in many of those models being ruled out because they

Aaron Beyen, Efe Hamamcı, Kasper Meerts, Dieter Van den Bleeken

We revisit and improve the analytic study arXiv:1804.03462 of spherically symmetric but dynamical black holes in Einstein's gravity coupled to a real scalar field. We introduce a series expansion in a small parameter $\epsilon$ that implements slow time dependence. At the leading order, the generic solution is a quasi-stationary Schwarzschild-de Sitter (SdS)

Yan Chang, Yukun Guo, Hongyu Liu, Deyue Zhang

This work is concerned with an inverse elastic scattering problem of identifying the unknown rigid obstacle embedded in an open space filled with a homogeneous and isotropic elastic medium. A Newton-type iteration method relying on the boundary condition is designed to identify the boundary curve of the obstacle. Based on the Helmholtz decomposition and the

Tom Bachmann

We establish a version of Gabber's presentation lemma in the setting of varieties with an action by the finite group of order 2.

Takaaki Ishii, Keiju Murata, Kentaroh Yoshida

We study the origin of turbulence on the string worldsheet with boundaries laid in anti de Sitter (AdS) spacetime. While the classical motion of a single closed string in AdS is integrable, it has recently been recognized that weak turbulence arises in the case of an open string suspended from the AdS boundary. In the open string case, it is necessary to imp

Chia-Yu Hung, Zhiqiang Hu, Yujia Hu, Roy Ka-Wei Lee

Authorship verification (AV) is a fundamental task in natural language processing (NLP) and computational linguistics, with applications in forensic analysis, plagiarism detection, and identification of deceptive content. Existing AV techniques, including traditional stylometric and deep learning approaches, face limitations in terms of data requirements and

Sepideh Mahabadi, Stojan Trajanovski

We study core-set construction algorithms for the task of Diversity Maximization under fairness/partition constraint. Given a set of points $P$ in a metric space partitioned into $m$ groups, and given $k_1,\ldots,k_m$, the goal of this problem is to pick $k_i$ points from each group $i$ such that the overall diversity of the $k=\sum_i k_i$ picked points is m

Veiko Palge, Christian Pfeifer

The Thomas--Wigner rotation (TWR) results from the fact that a combination of boosts leads to a non-trivial rotation of a physical system. Its origin lies in the structure of the Lorentz group. In this article we discuss the idea that the TWR can be understood in the geometric manner, being caused by the non-trivially curved relativistic momentum space, i.e.

William D. Harcourt, David G. Macfarlane, Duncan A. Robertson

Accurate, high-resolution 3D mapping of environmental terrain is critical in a range of disciplines. In this study, we develop a new technique, called the PCFilt-94 algorithm, to extract 3D point clouds from coarse resolution millimetre-wave radar data cubes and quantify their associated uncertainties. A technique to non-coherently average neighbouring wavef

Bobo Hua, Wendi Xu

In this paper, we study the nonlinear $p$-Laplacian equation $$-\Delta_{p} u+V(x)|u|^{p-2}u=f(x,u) $$ with positive and periodic potential $V$ on the lattice graph $\mathbb{Z}^{N}$, where $\Delta_{p}$ is the discrete $p$-Laplacian, $p \in (1,\infty)$. The nonlinearity $f$ is also periodic in $x$ and satisfies the growth condition $|f(x,u)| \leq a(1+|u|^{q-1}

Karthik Valmeekam, Matthew Marquez, Subbarao Kambhampati

There have been widespread claims about Large Language Models (LLMs) being able to successfully verify or self-critique their candidate solutions in reasoning problems in an iterative mode. Intrigued by those claims, in this paper we set out to investigate the verification/self-critiquing abilities of large language models in the context of planning. We eval

Xianghao Kong, Wentao Jiang, Jinrang Jia, Yifeng Shi

Vehicle-to-Everything (V2X) collaborative perception is crucial for autonomous driving. However, achieving high-precision V2X perception requires a significant amount of annotated real-world data, which can always be expensive and hard to acquire. Simulated data have raised much attention since they can be massively produced at an extremely low cost. Neverth

Takahiro Maeda, Keisuke Takeshita, Norimichi Ukita, Kazuhito Tanaka

For physical human-robot interactions (pHRI), a robot needs to estimate the accurate body pose of a target person. However, in these pHRI scenarios, the robot cannot fully observe the target person's body with equipped cameras because the target person must be close to the robot for physical interaction. This close distance leads to severe truncation and occ

Wenlong Ji, Lihua Lei, Asher Spector

Many causal estimands are only partially identifiable since they depend on the unobservable joint distribution between potential outcomes. Stratification on pretreatment covariates can yield sharper bounds; however, unless the covariates are discrete with relatively small support, this approach typically requires binning covariates or estimating the conditio

Phillip Karle, Felix Fent, Sebastian Huch, Florian Sauerbeck

Reliable detection and tracking of surrounding objects are indispensable for comprehensive motion prediction and planning of autonomous vehicles. Due to the limitations of individual sensors, the fusion of multiple sensor modalities is required to improve the overall detection capabilities. Additionally, robust motion tracking is essential for reducing the e

Sthavishtha R. Bhopalam, Jesus Bueno, Hector Gomez

Most passive droplet transport strategies rely on spatial variations of material properties to drive droplet motion, leading to gradient-based mechanisms with intrinsic length scales that limit the droplet velocity or the transport distance. Here, we propose droplet {\it fibrotaxis}, a novel mechanism that leverages an anisotropic fiber-reinforced deformable

Ilkka Törmä

Hex is a well known connection game in which two players attempt to connect opposite sides of the board by colored stones. In 2022, Hamkins and Leonessi introduced an infinite version, in which the goal is to construct a certain kind of two-way infinite path of adjacent stones. It was explicitly left open whether the winning condition is Borel. We prove that

Junlong Chen, Zhaoyang Qiu, Yanbin Tang

In this paper, we study the homogenization of the distribution-dependent stochastic abstract fluid models by combining the $two\!-\!scale$ convergence and martingale representative approach. A general framework of the homogenization research is established for stochastic abstract fluid models which are the type of nonlinear partial differential equations inc

Xiangyi Meng, Bin Zhou

Complex networks across various fields are often considered to be scale free -- a statistical property usually solely characterized by a power-law distribution of the nodes' degree $k$. However, this characterization is incomplete. In real-world networks, the distribution of the degree-degree distance $\eta$, a simple link-based metric of network connectivit

Gerard T. Schuster, Shihang Feng

We review four types of algorithms for physics-informed machine learning (PIML) inversion of geophysical data. The unifying equation is given by the joint objective function $\epsilon$: \begin{eqnarray} \epsilon^{||-PIML}&=&\lambda_1 \overbrace{||{\bf W}^{ML}({\bf H}_{{\bf w}} {\bf d}^{obs}-{\bf m})||^2}^{NN} + \lambda_2 \overbrace{{||{\bf W}^{FWI}({\bf L} {

Lixin Ge, Bingzhong Li, Hao Luo, Ke Gong

Dynamic tuning of optical cavities is highly desired in many photonic systems. Here, we show that Fabry-P\'{e}rot(FP) cavities can be actively controlled by the Casimir force. The optical FP cavities consist of a gold nanoplate confronted to an electrical-connecting multi-layer substrate in a liquid environment. The gold nanoplate can be stably suspended due

N. A. Abdulov, X. Chen, A. V. Kotikov, A. V. Lipatov

Based on a solution of DGLAP evolution equations at small values of Bjorken variable x, a simple analytic approximation for so-called linearly polarized gluon density \tilde{h}_1^{\perp g}(x,k_t^2, Q^2) is obtained at LO of perturbation theory.

Beier Zhu, Kaihua Tang, Qianru Sun, Hanwang Zhang

Foundation models like CLIP allow zero-shot transfer on various tasks without additional training data. Yet, the zero-shot performance is less competitive than a fully supervised one. Thus, to enhance the performance, fine-tuning and ensembling are also commonly adopted to better fit the downstream tasks. However, we argue that such prior work has overlooked

S. Huang, E. Griffin, J. Cai, B. Xin

Recent experiments demonstrated that proton transport through graphene electrodes can be accelerated by over an order of magnitude with low intensity illumination. Here we show that this photo-effect can be suppressed for a tuneable fraction of the infrared spectrum by applying a voltage bias. Using photocurrent measurements and Raman spectroscopy, we show t

Matthew Baas, Herman Kamper

Voice conversion aims to convert source speech into a target voice using recordings of the target speaker as a reference. Newer models are producing increasingly realistic output. But what happens when models are fed with non-standard data, such as speech from a user with a speech impairment? We investigate how a recent voice conversion model performs on non

Dawei Chen, Vinay Kerai, Matthew J. Alger, O. Ivy Wong

RadioTalk is a communication platform that enabled members of the Radio Galaxy Zoo (RGZ) citizen science project to engage in discussion threads and provide further descriptions of the radio subjects they were observing in the form of tags and comments. It contains a wealth of auxiliary information which is useful for the morphology identification of complex

Muhammad Razif Rizqullah, Ayu Purwarianti, Alham Fikri Aji

Nowadays, Question Answering (QA) tasks receive significant research focus, particularly with the development of Large Language Model (LLM) such as Chat GPT [1]. LLM can be applied to various domains, but it contradicts the principles of information transmission when applied to the Islamic domain. In Islam we strictly regulates the sources of information and

Junxiao Shen, John J. Dudley, Jingyao Zheng, Bill Byrne

Text entry is an essential task in our day-to-day digital interactions. Numerous intelligent features have been developed to streamline this process, making text entry more effective, efficient, and fluid. These improvements include sentence prediction and user personalization. However, as deep learning-based language models become the norm for these advance

Jianfei Ma

Future sequence represents the outcome after executing the action into the environment (i.e. the trajectory onwards). When driven by the information-theoretic concept of mutual information, it seeks maximally informative consequences. Explicit outcomes may vary across state, return, or trajectory serving different purposes such as credit assignment or imitat

Ajay Krishnan, V. S. Anoop

Climate change's impact on human health poses unprecedented and diverse challenges. Unless proactive measures based on solid evidence are implemented, these threats will likely escalate and continue to endanger human well-being. The escalating advancements in information and communication technologies have facilitated the widespread availability and utilizat

Jinghong Su, Lei Yi, Bidan Zhao, Cheng Wang

The presence of a dispersed phase can significantly modulate the drag in turbulent systems. We derived a conserved quantity that characterizes the radial transport of azimuthal momentum in the fluid-fluid two-phase Taylor-Couette turbulence. This quantity consists of contributions from advection, diffusion, and two-phase interface, which are closely related

Chao Feng, Alberto Huertas Celdrán, Janosch Baltensperger, Enrique Tomás Martínez Beltrán

Decentralized Federated Learning (DFL) emerges as an innovative paradigm to train collaborative models, addressing the single point of failure limitation. However, the security and trustworthiness of FL and DFL are compromised by poisoning attacks, negatively impacting its performance. Existing defense mechanisms have been designed for centralized FL and the

Tobias Schimanski, Julia Bingler, Camilla Hyslop, Mathias Kraus

Public and private actors struggle to assess the vast amounts of information about sustainability commitments made by various institutions. To address this problem, we create a novel tool for automatically detecting corporate, national, and regional net zero and reduction targets in three steps. First, we introduce an expert-annotated data set with 3.5K text

Xuan Zhang, Shu Sun, Meixia Tao, Qin Huang

In this paper, we consider a cooperative communication network where multiple low-Earth-orbit (LEO) satellites provide services to multiple ground users (GUs) cooperatively at the same time and on the same frequency. The multi-satellite cooperation has great potential in extending communication coverage and increasing spectral efficiency. Considering that th

Zijie Wu, Chaohui Yu, Zhen Zhu, Fan Wang

Recent progress in text-to-image (T2I) models enables high-quality image generation with flexible textual control. To utilize the abundant visual priors in the off-the-shelf T2I models, a series of methods try to invert an image to proper embedding that aligns with the semantic space of the T2I model. However, these image-to-text (I2T) inversion methods typi

Fa Peng, Yi Ru-Ya Zhang, Yuan Zhou

The exploration of shape metamorphism, surface reconstruction, and image interpolation raises fundamental inquiries concerning the $C^1$ and higher-order regularity of $\infty$-harmonic potentials -- a specialized category of $\infty$-harmonic functions. Additionally, it prompts questions regarding their corresponding approximations using $p$-harmonic potent

Haohan Weng, Tianyu Yang, Jianan Wang, Yu Li

Large image diffusion models enable novel view synthesis with high quality and excellent zero-shot capability. However, such models based on image-to-image translation have no guarantee of view consistency, limiting the performance for downstream tasks like 3D reconstruction and image-to-3D generation. To empower consistency, we propose Consistent123 to synt

Jianfei Ma

Temporal difference learning (TD) is a foundational concept in reinforcement learning (RL), aimed at efficiently assessing a policy's value function. TD($\lambda$), a potent variant, incorporates a memory trace to distribute the prediction error into the historical context. However, this approach often neglects the significance of historical states and the r

Peter Fiebig

For a root system R, a field K and a "choice of coefficients in K" we define a category of graded spaces with operators and study some of its properties. Then we assume that the coefficients are given by quantum binomials. We use basic arithmetic properties of binomial coefficients (such as q-versions of Lucas' theorem and the Pfaff-Saalsch\"utz identity) to

Pol Caselles, Eduard Ramon, Jaime Garcia, Gil Triginer

Recent advancements in learning techniques that employ coordinate-based neural representations have yielded remarkable results in multi-view 3D reconstruction tasks. However, these approaches often require a substantial number of input views (typically several tens) and computationally intensive optimization procedures to achieve their effectiveness. In this

Fengzhuo Zhang, Vincent Y. F. Tan, Zhaoran Wang, Zhuoran Yang

This paper studies two fundamental problems in regularized Graphon Mean-Field Games (GMFGs). First, we establish the existence of a Nash Equilibrium (NE) of any $\lambda$-regularized GMFG (for $\lambda\geq 0$). This result relies on weaker conditions than those in previous works for analyzing both unregularized GMFGs ($\lambda=0$) and $\lambda$-regularized M

Jože M. Rožanec, Gašper Petelin, João Costa, Blaž Bertalanič

In many cases, a machine learning model must learn to correctly predict a few data points with particular values of interest in a broader range of data where many target values are zero. Zero-inflated data can be found in diverse scenarios, such as lumpy and intermittent demands, power consumption for home appliances being turned on and off, impurities measu

Jason Hanson

The exterior algebra of Minkowski space naturally has the structure of a sixteen-dimensional Clifford algebra representation, and so can be used as the space of spinors. We examine plane, circular, and spherical solutions to the free Dirac equation in this extended notion of Minkowski space, and indicate how they can be used to obtain solutions to the standa

Luca Barbieri, Stefano Savazzi, Sanaz Kianoush, Monica Nicoli

Federated Learning (FL) methods adopt efficient communication technologies to distribute machine learning tasks across edge devices, reducing the overhead in terms of data storage and computational complexity compared to centralized solutions. Rather than moving large data volumes from producers (sensors, machines) to energy-hungry data centers, raising envi

Jose F. Gomez, Jose M. Torrelles, Josep M. Girart, Gabriele Surcis

We have carried out ALMA observations of the massive star-forming region W75N(B), which contains the massive protostars VLA1, VLA2, and VLA3. Particularly, VLA2 is an enigmatic protostar associated with a wind-driven H$_2$O maser shell, which has evolved from an almost isotropic outflow to a collimated one in just 20 years. The shell expansion seemed to be h

Ni Putu Intan Maharani, Ayu Purwarianti, Alham Fikri Aji

Clickbait spoiling aims to generate a short text to satisfy the curiosity induced by a clickbait post. As it is a newly introduced task, the dataset is only available in English so far. Our contributions include the construction of manually labeled clickbait spoiling corpus in Indonesian and an evaluation on using cross-lingual zero-shot question answering-b

Qiuhui Chen, Haiying Lyu, Xinyue Hu, Yong Lu

Recently, weakly-supervised image segmentation using weak annotations like scribbles has gained great attention in computer vision and medical image analysis, since such annotations are much easier to obtain compared to time-consuming and labor-intensive labeling at the pixel/voxel level. However, due to a lack of structure supervision on regions of interest

Junayed Mahmud, Nadeeshan De Silva, Safwat Ali Khan, Seyed Hooman Mostafavi

One of the most important tasks related to managing bug reports is localizing the fault so that a fix can be applied. As such, prior work has aimed to automate this task of bug localization by formulating it as an information retrieval problem, where potentially buggy files are retrieved and ranked according to their textual similarity with a given bug repor

Haoling Li, Jiuniu Wang, Zhiwei Wei, Wenjia Xu

Navigation and localization of UAVs present a challenge when global navigation satellite systems (GNSS) are disrupted and unreliable. Traditional techniques, such as simultaneous localization and mapping (SLAM) and visual odometry (VO), exhibit certain limitations in furnishing absolute coordinates and mitigating error accumulation. Existing visual localizat

Jie Ma, Long-Tu Yuan

The supersaturation problem for a given graph $F$ asks for the minimum number $h_F(n,q)$ of copies of $F$ in an $n$-vertex graph with $ex(n,F)+q$ edges. Subsequent works by Rademacher, Erd\H{o}s, and Lov\'{a}sz and Simonovits determine the optimal range of $q$ (which is linear in $n$) for cliques $F$ such that $h_F(n,q)$ equals the minimum number $t_F(n,q)$

Miao Zhu, Qiming Fu, Bo Liu, Mengxi Zhang

Radiotherapy is one of the primary treatment methods for tumors, but the organ movement caused by respiration limits its accuracy. Recently, 3D imaging from a single X-ray projection has received extensive attention as a promising approach to address this issue. However, current methods can only reconstruct 3D images without directly locating the tumor and a

Christian Partmann, Thorsten Naab, Antti Rantala, Anna Genina

We present a high resolution numerical study of the sinking and merging of massive black holes (MBHs) with masses in the range of $10^3 - 10^7 \, \mathrm{M}_\odot$ in multiple minor mergers of low mass dark matter halos without and with galaxies ($4\times 10^8 \, \mathrm{M}_\odot \lesssim \mathrm{M}_{\mathrm{halo}} \lesssim 2\times 10^{10} \, \mathrm{M}_\odo

Md Mushfiqur Rahman, Fardin Ahsan Sakib, Fahim Faisal, Antonios Anastasopoulos

Choosing an appropriate tokenization scheme is often a bottleneck in low-resource cross-lingual transfer. To understand the downstream implications of text representation choices, we perform a comparative analysis on language models having diverse text representation modalities including 2 segmentation-based models (\texttt{BERT}, \texttt{mBERT}), 1 image-ba

Kaare H. Jensen, Anneline H. Christensen

Exploring fluid-structure interactions is essential for understanding the physical principle underlying flow control in biological and man-made systems. Traditionally, we assume that the geometry is known, and from it, the solution to the coupled elastohydrodynamic problem is determined. Solving the inverse problem -- finding the geometry that leads to a des

Peng Xue, Quan Lin, Kunkun Wang, Lei Xiao

Dynamic behaviors of a physical system often originate from its spectral properties. In open systems, where the effective non-Hermitian description enables a wealth of spectral structures on the complex plane, the concomitant dynamics is significantly enriched, whereas the identification and comprehension of the underlying connections are challenging. Here w

Florencia Falkinhoff, Alexandre Ponomarenko, Jean-Lou Pierson, Lionel Gamet

In this study, we investigated the flow dynamics in a fixed bed of hydrogel beads using Particle Tracking Velocimetry to compute the velocity field in the middle of the bed for moderate Reynolds numbers. We discovered that despite the overall stationarity of the flow and relatively low Reynolds number, it exhibits complex multiscale spatial dynamics reminisc

Astha Agrawal, R. K. Sharma

This article explores additive codes with one-rank hull, offering key insights and constructions. The article introduces a novel approach to finding one-rank hull codes over finite fields by establishing a connection between self-orthogonal elements and solutions of quadratic forms. It also provides a precise count of self-orthogonal elements for any duality

Giorgio Piras, Maura Pintor, Ambra Demontis, Battista Biggio

Neural network pruning has shown to be an effective technique for reducing the network size, trading desirable properties like generalization and robustness to adversarial attacks for higher sparsity. Recent work has claimed that adversarial pruning methods can produce sparse networks while also preserving robustness to adversarial examples. In this work, we

Negin Mirzaie Dizaji

The invention of next-generation electrochemical energy devices (EEDs) has led to concerns about range anxiety, long recharge times, and moderate energy density. The behavior of cells and packs during fast charging depends on various factors, categorized into charging strategies and new materials. MXenes have gained significant attention since their discover